How Do We Think the COVID-19 Crisis Will Affect Our Careers (If Any Remain)? - IZA DP No. 13164 APRIL 2020
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DISCUSSION PAPER SERIES IZA DP No. 13164 How Do We Think the COVID-19 Crisis Will Affect Our Careers (If Any Remain)? Stijn Baert Louis Lippens Eline Moens Philippe Sterkens Johannes Weytjens APRIL 2020
DISCUSSION PAPER SERIES
IZA DP No. 13164
How Do We Think the COVID-19 Crisis
Will Affect Our Careers (If Any Remain)?
Stijn Baert Eline Moens
Ghent University, University of Antwerp, Ghent University
Université catholique de Louvain, IZA and
IMISCOE Philippe Sterkens
Ghent University
Louis Lippens
Ghent University Johannes Weytjens
Ghent University
APRIL 2020
Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may
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53113 Bonn, Germany Email: publications@iza.org www.iza.orgIZA DP No. 13164 APRIL 2020
ABSTRACT
How Do We Think the COVID-19 Crisis
Will Affect Our Careers (If Any Remain)?*
This study is the first in the world to investigate the expected impact of the COVID-19 crisis
on career outcomes and career aspirations. To this end, high-quality survey research with a
relevant panel of Belgian employees was conducted. About 21% of them fear losing their
jobs due to the crisis—14% are concerned that they will even lose their jobs in the near
future. In addition, 26% expect to miss out on promotions that they would have received
had the COVID-19 crisis not occurred. This fear of a negative impact is higher in vulnerable
groups, such migrants. In addition, we observe that many panel members believe they
will look at the labour market differently and will have different work-related priorities in
the future. In this respect, more than half of the panel members indicate that they have
attached more importance to working conditions and work-life balance since the COVID-
19 crisis.
JEL Classification: J63, J62, J30, J41, J15, J16
Keywords: COVID-19, careers, employment, career aspirations
Corresponding author:
Stijn Baert
Ghent University
Sint-Pietersplein 6
9000 Gent
Belgium
E-mail: Stijn.Baert@UGent.be
* We are grateful to Simon Amez, Brecht Neyt, and Hannah Van Borm for their help in promoting the survey, and
to Erik Meersseman and Anja Termote (both from the General Directorate of Statistics—Statistics Belgium) for their
constructive support in providing data for the post-stratification of the sample.1. Introduction
Respected international organisations agree that the current COVID-19 crisis will have a
tremendous impact on society, both in the short and in the long term (ILO, 2020; Remuzzi
& Remuzzi, 2020; WHO, 2020). In March and April of 2020, hospitals in several countries
have been operating at their maximum capacity, and thousands of deaths have occurred.
These countries have also gone into lockdown to varying degrees, which means that people
have to live in social isolation from each other (Giupponi & Landais, 2020; Remuzzi &
Remuzzi, 2020; WHO, 2020). Based on systems of ‘temporary unemployment’, employment
contracts have been suspended in companies that are unable to comply with social
distancing directives, or which have experienced an immediate fall in demand for their
products and services (Giupponi & Landais, 2020; ILO, 2020). In the longer term, there is a
fear that what began as a health crisis will develop into a deep economic crisis, with a decline
in growth in the long term and increasing unemployment (Atkeson, 2020; Giupponi &
Landais, 2020; ILO, 2020; McKibbin & Fernando, 2020).
However, the quantitative predictions about the long-term, global impact of the COVID-
19 crisis on the economy and labour market in the OECD countries vary dramatically. This is
not surprising. Since standard economic models are trained using data from ‘normal times’,
making predictions concerning ‘abnormal times’ is challenging for economic research.
Moreover, the extent to which the supply side of the labour market will react to this health
shock is unclear, particularly whether employees will adjust their labour preferences and
corresponding behaviours.
To the best of our knowledge, the present research is the first study in the world to
investigate the expected impact of the COVID-19 crisis on career outcomes and career
aspirations using standardised measurements. Specifically, a panel of 3,821 employees,
representative by gender, age and education—two levels for each of these three
characteristics—of the broader population of employees, was surveyed with regard to two
research questions.
Research question 1 (RQ1): What do employees think the impact of the COVID-19 crisis
will be on their careers?
2Research question 2 (RQ2): What do employees think the impact of the COVID-19 crisis
will be on the importance they attach to various job characteristics?
We seek answers to these questions not only for our panel in general but also investigate
the extent to which the perceived impact on careers differs according to personal and job
characteristics. In this way, we aim to inform policy makers about the important fears and
opportunities related to the current COVID-19 crisis. In addition, our study provides insight
into those groups that require special attention in this regard during this and subsequent
health shocks.
2. Data
2.1 Research population and sampling
Our research population is formed by employees in Flanders, the largest of the three Belgian
regions, who are under the age of 65, which is the legal retirement age in Belgium. This
delineation is in line with our research focus on employees (versus the self-employed) and
allowed us to compare the sample’s characteristics with population averages, as discussed
below.
The labour market in Flanders is characterised by two main features. First, the
competition for human capital is relatively high in comparison to other regions in Europe
(Baert & Verhaest, 2019; Gerard & Valsamis, 2015). In the fourth quarter of 2019, the job
vacancy rate—that is, the number of vacancies as a percentage of the sum of this number
and the number of occupied jobs—was 3.9% in Flanders, while it was 2.2% in the EU-27
(source: General Directorate of Statistics—Statistics Belgium). Second, labour contracts are
highly regulated (Baert & Verhaest, 2019). Overall, the employment rate for the entire
population of Flanders aged 20 to 64 was 75.5% in the fourth quarter of 2019, while it was
70.5% in the EU-27 (source: Eurostat and General Directorate of Statistics—Statistics
Belgium).
As of the 14th of April 2020, Belgium had 31,119 confirmed cases of COVID-19 (Mortgat,
2020a). A slight majority (59%) of the infected people lived in Flanders. Therefore, at the
3time of writing, 0.27% of the population was infected, which made Belgium the fifth worst
affected country in terms of infections per capita (ECDC, 2020). Since the 11th of March
2020, basically only hospitalised patients and medical personnel have been tested for
COVID-19 (Mortgat, 2020b). Accordingly, the reported numbers should be considered as
lower bounds and not as true values. Belgium has been in lockdown since the 18th of March
2020. Citizens are only allowed to leave their residences to purchase essential groceries.
Working is allowed, but all firms are asked to allow most of their employees to work from
home. When this is not possible, only firms that respect the social distancing rules can allow
their employees to continue working. Despite the policy to allow people to continue
working, COVID-19 is causing a tremendous increase in unemployment. In response, the
national employment office has simplified the procedure for requesting unemployment
benefits to a significant degree. While no detailed statistics were available at the time of
writing, at least 1,258,000 people have been confirmed as registering as ‘temporarily
unemployed’ in Belgium by the 1st of April 2020 (source: Eurostat and General Directorate
of Statistics—Statistics Belgium) which, compared to the size of the labour force, is a
substantially higher figure than are the comparable numbers in France and Germany
(Remuzzi & Remuzzi, 2020). In addition, this number is expected to increase slightly because
the deadline for filing for temporary unemployment due to COVID-19 is the 19th of April.
Under ideal research circumstances, the ‘first-best’ option to arrive at a representative
sample of our population would have been to draw a probability sample from all Flemish
employees under the age of 65. If we had been able to draw such a—sufficiently large—
sample and have the participants answer our survey effectively—this second condition is
often not met in studies that label their data as representative—we would be confident that
all the reported findings would be perfectly representative of our population (Bethlehem &
Biffignandi, 2012; Fowler, 2014; Tourangeau, Conrad, & Couper, 2013). However, this
sampling procedure is only possible at a high cost and within a long-term research project
(for example, through sampling via the national register, after ethical approval, and the
follow-up by the register office of non-responses of the participants), which was neither
feasible nor desirable in our case because we wanted to inform the scientific community
and policy makers about career expectations at the micro level as quickly as possible.
Our research was based on a web survey. This method of data gathering has several
4advantages. For example, as respondents are able to determine the timing and pace of web
surveys themselves, and because they can reread questions easily, they will give more
reliable and valid answers compared to when engaging in physical or telephonic interviews
(Bethlehem & Biffignandi, 2012; Tourangeau et al., 2013). However, there are also two
important drawbacks with the use of web surveys (Bethlehem and Biffignandi, 2012;
Tourangeau et al., 2013). The first is the problem of the under-representation of groups that
do not have access to the Internet (‘undercoverage’). However, calculations based on the
European Social Survey (round 9 of 2018) show that the distortion caused by this problem
is negligible, as the number of Belgian employees under the age of 65 who never use the
Internet is only 1%—in addition, 96% indicate that they use the Internet several times per
week and 3% indicate to do so less frequently. In order to address this issue further, in our
calls for the survey, which were supported by the largest Belgian newspaper, we repeatedly
underlined that we hoped that readers of our call would not only complete the survey
themselves, but would also encourage their less digital-savvy acquaintances to do so.
A more important problem that compromises the overall representativeness of our
sample—and that of almost all web surveys—is linked to the fact that the respondents
themselves chose whether or not to participate in our survey (‘self-selection’). The answers
of those who actually participated might be different from the responses of those who did
not chose to complete the survey. Therefore, to enhance the representativeness of our
survey, we followed the strategy of post-stratification, as recommended by Bethlehem and
Biffignandi (2012) and Tourangeau et al. (2013), two seminal works on web surveys. Under
certain conditions (see below), this strategy completely eliminates any bias caused by self-
selection (and under-representation); in practice, empirical work has found that, on
average, the strategy leads to significant reductions in bias (Tourangeau et al., 2013).
In our case, post-stratification entailed the selection of a sub-sample of 3,821 individuals
resembling the population of Flemish employees under 65 years of age in terms of (i)
gender, (ii) age, and (iii) education level from our total sample of 14,005 respondents. These
three ‘auxiliary variables’ were hypothesised—and found, as discussed below—to have
great predictive power with regard to the constructs we wished to investigate in the context
of answering RQ1 and RQ2. Specifically, we aimed for representativeness by two levels for
each of these three variables: males versus females, tertiary education versus no tertiary
5education and being younger or older than 50. By combining these levels, we created eight
—two times two times two—cells (‘strata’) amongst which we wanted to realise a balance.
Including more strata was found to be inappropriate because it resulted in an insufficient
number of individuals per stratum (Bethlehem & Biffignandi, 2012; Tourangeau et al., 2013).
Next, we identified the stratum that was most underrepresented in comparison to
population averages for all Flemish employees under 65 years of age in 2019 (figures
provided by the General Directorate of Statistics—Statistics Belgium). This was revealed to
be the stratum of female workers without a tertiary education diploma and aged 50 or older.
All the individuals with complete answers who met our inclusion criteria were included in
the final panel for this stratum. For the other seven strata, individuals were selected
randomly according to their proportions in the population (compared to females without a
tertiary education diploma and aged 50 or older). Accordingly, our panel, like the wider
population, consists of:
(i) 22.2% (13.7%) males without (with) tertiary education qualifications being younger
than 50;
(ii) 9.8% (5.4%) males without (with) tertiary education qualifications being older than
50;
(iii) 15.6% (19.3%) females without (with) tertiary education qualifications being
younger than 50; and
(iv) 8.3% (5.7%) females without (with) tertiary education qualifications being older than
50.
The results presented below are robust against analysing alternative random selections for
the seven strata with an abundant supply in the full sample.
The assumption under which this post-stratification resolves the potential self-selection
bias is that, within the strata that were formed, there is no longer a link between the chance
of participating in the survey (selecting oneself to participate) on one hand, and the answers
given for the central outcome variables of the survey on the other (the ‘missing at random’
assumption; Bethlehem & Biffignandi, 2012; Little & Rubin, 2002; Tourangeau et al., 2013).
An indication of the extent to which the ‘missing at random’ assumption is acceptable is the
strength of the relationship between the auxiliary variables used for the post-stratification
and the outcome variables of the survey (Bethlehem & Biffignandi, 2012). A regression
analysis showed that the characteristics across which we stratified did indeed have strong
6predictive power for many of the surveyed variables related to RQ1 and RQ2. For example,
as can be seen in Table B1 in Appendix B, gender is a strong predictor of the fear of losing
one’s job due to the COVID-19 crisis (p < 0.001 if no further control variables are included;
p = 0.001 if controlling for all other personal and job characteristics adopted in the
questionnaire).
The results of the regression analyses presented below can be seen as an additional
effort to address the potential self-selection bias, as these analyses indicate how our
outcome variables evolve for different values of the auxiliary variables (‘generalised
regression estimation’; Bethlehem & Biffignandi, 2012; Tourangeau et al., 2013).
2.2 Survey
The on-line survey was available for completion via Qualtrics between Wednesday 25 March
2020 and Tuesday 31 March 2020 via Qualtrics. The survey consisted of seven parts. First,
two introduction screens were displayed. On the first introduction screen,
(i) the objective of the survey was explained (investigating the expected impact of the
COVID-19 crisis on the careers of salaried employees);
(ii) the survey population was clarified; and
(iii) the incentives for completing the questionnaire were underlined (that is,
committing oneself to important social research and having a chance of winning one
of the 16 prizes to be raffled, with a combined value of EUR 688.40).
On the second introduction screen, respondents were informed about anonymised data
processing and their rights as research participants in accordance with the GDPR guidelines
at Ghent University, and were asked to agree to these modalities, thus providing their
‘informed consent’.
Second, the respondents were asked about their current work situation (employee,
temporarily unemployed [due to the COVID-19 crisis], self-employed, classically
unemployed, or inactive). Only those who fell into one of the first two categories could
participate in the survey, in accordance with the call for this research.
In the third part, the respondents were questioned about the expected effects of the
COVID-19 crisis for their careers. Specifically, the following seven potential fears were
7evaluated:
(i) losing job in the short or long term;
(ii) losing job in the short term;
(iii) missing out on promotion;
(iv) overall negative impact on career;
(v) negative impact on wage;
(vi) negative impact on personal motivation; and
(vii) negative impact on the number of attractive vacancies.
In the fourth part, the respondents were questioned about the expected impact of this crisis
on the extent to which they attached importance to a series of job characteristics.
Specifically, they were asked to share whether they would attach more or less importance
to the following seven aspects of a possible new job as a result of the COVID-19 crisis:
(i) wage;
(ii) employment relationship;
(iii) job content;
(iv) working conditions;
(v) work-life balance;
(vi) distance to the workplace; and
(vii) possibility of teleworking.
Given the central position of the two latter parts of the survey within the context of the
present article—these two parts delineate the outcome variables related to RQ1 and RQ2—
the items adopted are included in Appendix A.
Then, in the fifth part, the respondents were asked about their experiences,
expectations and hopes with regard to (extended) telework (in the context of the COVID-19
crisis). These items have not been evaluated in the context of the present study, except for
(i) the candidates’ assessments of the percentage of their work that could potentially be
done via telework and (ii) an indicator of whether they had had to telework to an extended
degree due to the COVID-19 crisis at the time of the survey. These variables were included
in our analyses as potential moderators of expected career consequences (RQ1) and
perceived evolutions in job priorities (RQ2).
In the sixth part of the survey, we gathered information about the personal
characteristics of our respondents and the characteristics of their jobs in order to also
8investigate heterogeneity in the answers to RQ1 and RQ2 by these characteristics.
Specifically, we gathered information concerning the respondents’ gender, age, migration
background, education level, relationship status, number of resident children (and other
persons), province and degree of urbanisation of their residence, and health status (prior to
the COVID-19 crisis, overall current status and status as a COVID-19 patient), as well as their
type of employment contract, the part-time nature of this contract, their tenure (with the
current employer and in the current job), their level of job satisfaction experienced, four key
characteristics of their job (autonomy, dependency on others, interaction outside of the
organisation and feedback from others), and their sector of employment. The scales used
(and their sources) are clarified in Table 1.
Finally, in the seventh part of the survey, participants were presented with final screens
on which they (i) were thanked for their participation and (ii) could leave their email address
in the context of participation in future research and/or the lottery of prizes linked to full
participation (as mentioned above).
Several precautions were taken to ensure the reliability and validity of the measuring
instrument. In general, the guidelines in Bethlehem and Biffignandi (2012), Fowler (2014)
and Tourangeau et al. (2013), which are seminal handbooks concerning the drafting of
questionnaires (for off-line and on-line surveys), were taken into account as far as possible
when designing the questionnaire. In the following paragraphs, we discuss some of the
decisions taken in this regard.
To counteract the problem of ‘non-differentiation’, whereby respondents, usually out
of fatigue, start to fill in anything (Bethlehem & Biffignandi, 2012), the number of items
within the same cluster and screen was limited. Moreover, all the items were formulated
comprehensibly, did not contain double-barrelled constructions or negations, and
complicated wording was avoided as far as possible (Lietz, 2010; McPherson & Mohr, 2005).
As related research has indicated that rewarding respondents who complete surveys in full
leads to better quality data (Göritz, 2006; Tourangeau et al., 2013), raffle prizes were offered
to the participants (as mentioned earlier). In addition, to encourage them to complete the
questionnaire in full, a progress indicator for the questions was added (Bethlehem &
Biffignandi, 2012). Certain important words were presented in bold text (Tourangeau et al.,
2013).
9In addition, we followed the advice of Weijters, Cabooter, and Schillewaert (2010) with
regard to response scales for research amongst the general public by using five-point Likert
scales for the different items whenever possible. These scales usually comprised the answer
options ‘completely disagree’, ‘somewhat disagree’, ‘neutral’, ‘somewhat agree’, and
‘completely agree’. There is no agreement on the use of ‘somewhat’ in the scientific
literature. An argument for including it is that omitting it can lead to confusion. ‘Disagree’
can then be seen as the end point of the scale. For example, a respondent may (simply) not
agree with the statement; whether he or she would ‘completely disagree’ or ‘[just] disagree’
may not be substantially different for some respondents, but completely different for
others. This confusion may result in less frequent selection of the extremes, which may lead
to ‘restriction of range’ (that is, the limitation of the probability of selecting certain response
options).
Since we preferred to not only present regression analyses but also histograms capturing
all the response options and their frequencies (see the results section), it was important, in
accordance with the advice of Weijters et al. (2010), to label all response options. Moreover,
in line with the recommendation of Weijters and Baumgartner (2012), positively formulated
items and negatively formulated items were alternated, as were regular-phrased and
reversed-phrased items. In this way, the problem of ‘acquiescence’ (Bethlehem &
Biffignandi, 2012), whereby some respondents feel a strong tendency to agree with
statements because they stop reading the questions meticulously at a certain point, was
partly overcome. Finally, we deliberately did not include the option ‘I do not know’ to
prevent respondents from selecting this option quickly to avoid having to think about their
actual responses (Bethlehem & Biffignandi, 2012).
The measuring instrument was refined on the basis of pilot tests, in several rounds,
amongst 55 respondents. All feedback was recorded. In the later rounds, the focus was on
the following questions:
(i) ‘Was it clear what was expected in each question?’
(ii) ‘Were there words or phrases that were unclear or difficult to understand?’ and
(iii) ‘Were there any crucial questions we forgot to pose given the aims of the survey?’
A ‘trap question’ was added to the questionnaire to test the participants’ attentiveness.
Inattentive participants were not included in the cleaned dataset (and were therefore not
10eligible to be included in the panel on which the results in this article are based). In the
sensitivity analyses, respondents with the 5% shortest survey duration (that is, less than 6
minutes and 9 seconds) were excluded from the panel. These exclusions did not change the
results noticeably. The median time the panel took to complete the survey was 10 minutes
and 27 seconds. This median duration indicates that the duration of the survey was
sufficiently limited to prevent ‘satisficing’; that is, less attentive answering of items, usually
due to fatigue (Bethlehem & Biffignandi, 2012).
In Table 1, we provide the reader with some summary statistics concerning the resulting
data.
3. Results
3.1 Perceived career-related fears induced by the COVID-19 crisis
Figure 1 provides an overview of the panel members’ responses to the items in the survey
related to RQ1. Table 2 summarises the results of a regression analysis in which these
responses were classified according to the personal and job characteristics surveyed. Linear
regression analyses in which the standard errors were corrected for heteroscedasticity
(White correction) were performed. Ordered logistic models and dummy specifications for
the continuous explanatory variables included led to the same research insights. In addition,
we computed multicollinearity diagnostics leading to variance inflation factors lower than
10 for each of the models presented. The complete regression results for the first item are
included in Table A1 in Appendix A.
As can be seen in Figure 1 and Table 2, more than one in five (21.1%) of the panel
members indicate to be afraid of losing their job due to the COVID-19 crisis. About one out
of seven (13.7%) fear that this will even be the case before the end of the year. This fear is
significantly more apparent in vulnerable groups, such as older employees and migrants.
11This is in line with scientific research that indicates that the employment of disadvantaged
groups is more sensitive to the economic cycle, and that discrimination on the labour market
is greater when labour market tightness within occupations is lower (Baert, Cockx, Gheyle,
& Van Damme, 2015; Immervoll, Peichl, & Tatsiramos, 2011). Based on the further analysis
of the data, the fear of losing one’s job permanently increases to four out of ten amongst
the temporarily unemployed. This is somewhat in line with the scientific literature on the
scarring effects of unemployment (Baert & Verhaest, 2019; Cockx & Ghirelli, 2016; Van Belle,
Di Stasio, Caers, de Couck, & Baert, 2018).
Moreover, about one in four (26.2%) respondents fear to missing out on a promotion
he or she would have received had the COVID-19 crisis not occurred. This fear is significantly
higher amongst migrants and those who are currently temporarily unemployed, and
significantly lower amongst those working in the public sector. One in two (49.9%) also fear
a direct, negative effect of the crisis on their wages. This fear is significantly higher amongst
those who have temporary contracts in the private sector or are currently temporarily
unemployed. More than one in four (27.5%) fear an impact on their personal work
motivation. This estimated impact is significantly higher amongst, inter alia, younger people.
In addition, more than half (51.9%) fear that the COVID-19 crisis will have a negative
impact on the number of vacancies that might interest them. This fear of fewer attractive
vacancies is significantly higher amongst highly educated people. This may seem surprising
at first sight, but it might simply indicate that people with lower levels of education already
feared a decline in the number of attractive vacancies before the COVID-19 crisis struck,
given the reports of fewer job opportunities available to them due to digitisation and
automation (Autor, 2015; De Vos, 2018; Howard, 2019; Nedelkoska & Quintini, 2018).
The results described above illustrate the general fear of negative career consequences
due to the COVID-19 crisis well. Similarly, about one in three (33.6%) fear an overall negative
impact on their careers. In this respect, two sectors hit particularly hard are tourism and
catering. Tourism worldwide faces an unprecedented setback due to the current COVID-19
crisis, as the World Tourism Organisation (UNWTO, 2020) expects global tourism to fall by
20% to 30% this year compared to last year (figures as of 24 March 2020). In addition, the
Flemish federation of pub, restaurant and hotel owners (‘Horeca Vlaanderen’) foresees
similar declines in tourism and catering (Snick, 2020). This negative impact on tourism and
12catering businesses, and by extension employers, also translates to the workforce, for
whom, according to our results, the fear of overall negative career consequences is
significantly higher than it is for employees working in most other sectors.
As a final remark, we observe that job satisfaction and on-the-job feedback both have
positive impacts on the views of our respondents with regard to the effects of the COVID-
19 crisis on future career outcomes. Both variables are related to significantly lower levels
of fear regarding job losses, general negative career consequences, declining wages and
fewer attractive vacancies. Furthermore, job satisfaction is also related to significantly lower
levels of fear with regard to missing out on promotions and less work motivation. Previous
research has underlined the positive relationships between the feedback environment (that
is, all the relevant cues that provide information about the performance of an individual)
and job satisfaction (Anseel & Lievens, 2007), and between feedback-seeking behaviour and
extrinsic (objective) career success measured by wages or promotions (Cheramie, 2013).
Based on our results, knowing where one stands and how one’s job performance is
estimated by others thus appears to have, in addition, a positive influence on self-reported
career prospects under the precarious circumstances of the current crisis.
3.2 Perceived evolution in attaching importance to particular job
aspects induced by the COVID-19 crisis
The survey items relating to RQ2 are analysed by analogy with those discussed in the
previous subsection. As can be seen in Figure 2 and Table 3, only about one in five (20.6%)
respondents from our panel indicate that they will attach more importance to wages due to
the COVID-19 crisis, assuming that they were to seek new jobs in the foreseeable future.
Conversely, almost seven out of ten (69.3%) panel members responded neutrally to the
corresponding item. By contrast, more than half indicate to attach more importance to
working conditions (51.8%) and work-life balance (51.1%) now, and almost one in two
(48.1%) perceive the possibility of teleworking becoming more important following the
COVID-19 crisis. The latter statistic is significantly higher for women and younger employees.
Furthermore, just over two out of five attach more importance to the extent to which
employers take their personal wishes into account (41.7%), and to the distance from the
workplace to home (41.2%). The latter is significantly higher for older employees.
13These results are in line with previous research that showed that pay is a necessary but
not an imperative condition to remain motivated at work, as providing feedback and social
recognition also play key roles in this relationship (Stajkovic & Luthans, 2003). Social
recognition is mainly highlighted by our respondents in terms of contextual factors, such as
work-life balance, working conditions and employer rapport (see above), which are
allocated more importance. The sudden changes as a result of the current crisis, including
the abrupt introduction of compulsory teleworking for almost all non-essential occupations
in Belgium (Federale Overheidsdienst Binnenlandse Zaken, 2020), probably played a
substantial role in the increased reports of the importance thereof.
4. Conclusion
We investigated the expected impact of the COVID-19 crisis on career outcomes and career
aspirations via standardised survey research on Flemish employees. We found the fear of
negative career impacts due to the COVID-19 crisis to be significant. More than one in four
of our panel members indicate to fear losing their jobs because of the crisis. One in seven
fear that this will be the case even before the end of the year. It is also striking that one in
four fear missing out on a promotion that she/he would have received had the COVID-19
crisis not occurred. The fear of negative impacts is greater in vulnerable groups, such as
migrants. In addition, we observed that many panel members believe they will look at the
labour market differently and will have different work-related priorities in the future. More
than half of the panel members indicate attaching more importance to working conditions
and work-life balance since the onset of the COVID-19 crisis.
We end this article with a brief discussion of the limitations of the research. First, as
described, we made a great effort to be able to present research results obtained from a
relevant panel of employees in the short term. Using post-stratification, we ensured that
our panel was representative of our broader research population by using (two levels of)
gender, age and educational level. As indicated, we have good reasons to believe that our
way of working limited the non-response bias in our results, but we cannot claim that it has
14been reduced to 0.
Second, the findings cannot be read as an objective prediction of the impact of the
COVID-19 crisis on the careers and career aspirations of employees in Flanders, let alone in
the Western world as a whole. The results provide an insight into how Flemish employees
think about this impact in the midst of this crisis. In this regard, the extent to which the
measured intentions will be realised—or will remain only good intentions, as is often the
case with intentions made around New Year’s Eve or after a serious illness—is uncertain.
Nevertheless, we believe the mapped fears and perceived evolutions in career aspirations—
and heterogeneity both by personal and job characteristics—are relevant to policy makers,
as well as to the scientific community. We hope that, based on other research strategies,
the latter will reveal whether the outlined fears were justified and whether the expected
impact on career aspirations was realised in reality in the medium term.
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19Appendix A: Survey items concerning outcome variables
A.1 Perceived career-related fears induced by the COVID-19 crisis
The following statements are about how you think the current corona crisis will affect your
future career once you have returned to normal work. Please indicate to what extent you
agree with the statements on a scale from ‘completely disagree’ (1) to ‘completely agree’
(5).
(Losing job in the short or long term) I am afraid the current corona crisis will cause me
to lose my current job in the short or long term.
(Losing job in the short term) I am afraid the current corona crisis will cause me to lose
my current job before the end of 2020.
(Missing out on promotion) I am afraid the current corona crisis will result in me not
getting a promotion that I would otherwise have received.
(Overall negative impact on career) I am afraid the current corona crisis will have a
negative impact on my overall career.
(Negative impact on wage) I am afraid the current corona crisis will have a negative
impact on my wage.
(Negative impact on personal motivation) I am afraid the current corona crisis will have
a negative impact on my personal work motivation.
(Negative impact on the number of attractive vacancies) I am afraid the current corona
crisis will have a negative impact on the number of job vacancies that might interest me.
A.2 Perceived evolution in attaching importance to particular job
aspects induced by the COVID-19 crisis
Imagine you were to look for a job again in the future (for example, after resignation or
because you are ready for a new challenge). Do you think that the current corona crisis will
cause you to attach greater or lesser importance to the following aspects of a potential new
job? Scale: certainly less important (1), somewhat less important (2), as important as before
20the corona crisis (3), somewhat more important (4), certainly more important (5).
(Wage) The wage I can earn in the new job.
(Employment relationship) The extent to which my new employer takes my personal
wishes into account.
(Job content) The content of the new job.
(Working conditions) The circumstances in which I have to work in the new job.
(Work-life balance) The extent to which the new job allows me to maintain a good work-
life balance.
(Distance to the workplace) The distance between my residence and my new workplace.
(Possibility of teleworking) The extent to which I can work from home.
Appendix B: Additional tables
21Figure 1. Perceived Career-Related Fears Induced by the COVID-19 Crisis: Answers Given
0.0% 10.0% 20.0% 30.0% 40.0% 50.0%
33.6%
32.0%
I am afraid the current corona crisis will cause me
13.3%
to lose my current job in the short or long term
15.9%
5.2%
44.5%
29.3%
I am afraid the current corona crisis will cause me
12.5%
to lose my current job before the end of 2020
9.8%
3.9%
27.7%
I am afraid the current corona crisis will result in 19.3%
me not getting a promotion that I would 26.7%
otherwise have received 17.8%
8.5%
20.1%
29.2%
I am afraid the current corona crisis will have a
17.2%
negative impact on my overall career
25.7%
7.8%
15.7%
19.3%
I am afraid the current corona crisis will have a
15.2%
negative impact on my wage
32.4%
17.5%
29.5%
30.5%
I am afraid the current corona crisis will have a
12.4%
negative impact on my personal work motivation
20.9%
6.6%
10.5%
I am afraid the current corona crisis will have a 12.7%
negative impact on the number of job vacancies 24.9%
that might interest me 33.0%
18.9%
Completely disagree Somewhat disagree Neutral Somewhat agree Completely agree
22Figure 2. Perceived Evolution in Attaching Importance to Particular Job Aspects Induced by
the COVID-19 Crisis: Answers Given
Imagine you were to look for a job again in the future (for example, after resignation or because you are
ready for a new challenge). Do you think that the current corona crisis will cause you to attach greater or
lesser importance to the following aspects of a potential new job?
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
1.0%
9.1%
The wage I can earn in the new job 69.3%
14.4%
6.2%
0.7%
The extent to which my new employer takes my 6.5%
51.1%
personal wishes into account 30.9%
10.8%
0.5%
5.0%
The content of the new job 57.6%
26.1%
10.7%
0.3%
The circumstances in which I have to work in the 3.6%
44.3%
new job 37.0%
14.8%
0.2%
The extent to which the new job allows me to 3.5%
45.2%
maintain a good work-life balance
31.0%
20.1%
0.8%
The distance between my residence and my new 5.3%
52.7%
workplace
22.8%
18.3%
5.6%
10.1%
The extent to which I can work from home 36.2%
31.3%
16.7%
Certainly less important
Somewhat less important
As important as before the corona crisis
Somewhat more important
Certainly more important
23Table 1. Summary Statistics (N = 3,821)
Female 0.488 (–)
Age 41.682 (10.851)
Migration background 0.027 (–)
Tertiary education 0.441 (–)
Single 0.202 (–)
In a relationship but not cohabiting 0.072 (–)
In a relationship and cohabiting 0.726 (–)
Number of resident children 0.911 (1.047)
Resident parents 0.077 (–)
Resident family members (other than parents) 0.038 (–)
Resident others (not family) 0.020 (–)
Province of Antwerp 0.279 (–)
Province of West Flanders 0.187 (–)
Province of East Flanders 0.307 (–)
Province of Limburg 0.075 (–)
Province of Flemish Brabant 0.152 (–)
Living in the countryside or rural area 0.358 (–)
Living in the centre of a village 0.272 (–)
Living in the suburbs of a city 0.225 (–)
Living in the centre of a city 0.146 (–)
Health before the COVID-19 crisis (scale) 4.106 (–)
Current health (scale) 3.910 (–)
Never been a COVID-19 patient (definitely or likely) 0.708 (–)
Uncertain about having been a COVID-19 patient 0.222 (–)
COVID-19 patient at the moment (definitely or likely) 0.037 (–)
COVID-19 patient in the recent past (definitely or likely) 0.033 (–)
Employed via a temporary contract in the private sector 0.041 (–)
Employed via a permanent contract in the private sector 0.787 (–)
Employed via a regular contract in the public sector 0.078 (–)
Employed via a permanent appointment in the public sector 0.093 (–)
Part-time contract 0.181 (–)
Tenure with current employer (scale) 2.915 (1.444)
Tenure in current job (scale) 2.471 (1.336)
Satisfied with job (scale) 3.992 (0.930)
Autonomous in job (scale) 3.774 (1.189)
Dependent on others in job (scale) 3.155 (1.107)
Interaction outside of the organisation in job (scale) 3.567 (1.393)
Feedback from others in job (scale) 3.065 (1.168)
Sector: Purchasing 0.010 (–)
Sector: Administration 0.071 (–)
Sector: Construction 0.033 (–)
Sector: Communication 0.016 (–)
Sector: Creative 0.008 (–)
Sector: Provision of services 0.076 (–)
Sector: Financial 0.050 (–)
Sector: Health 0.055 (–)
Sector: Catering and tourism 0.035 (–)
Sector: Human Resources 0.043 (–)
24Sector: ICT 0.072 (–)
Sector: Legal 0.014 (–)
Sector: Agriculture and horticulture 0.003 (–)
Sector: Logistics and transport 0.074 (–)
Sector: Management 0.040 (–)
Sector: Marketing 0.017 (–)
Sector: Maintenance 0.018 (–)
Sector: Education 0.038 (–)
Sector: Research and development 0.025 (–)
Sector: Government 0.047 (–)
Sector: Production 0.069 (–)
Sector: Technology 0.040 (–)
Sector: Sales 0.099 (–)
Sector: Other 0.048 (–)
Temporarily unemployed 0.197 (–)
% of work potentially done via telework 42.795 (36.579)
Temporarily extended telework 0.503 (–)
Notes. No standard deviations are presented for binary variables. The levels (and
values) for the health scales are: very bad (1), somewhat bad (2), neither bad nor
good (3), somewhat good (4), and very good (5). The levels for the tenure scales
are: less than 2 years (1), between 2 and 5 years (2), between 6 and 10 years (3),
between 11 and 20 years (4), and more than 20 years (5). The levels for the job
scales are: completely disagree (1), somewhat disagree (2), neutral (3), somewhat
agree (4), and completely agree (5). The operationalisation of these variables is
based on Amez, Vujić, Soffers, and Baert (in press), Baert, Verhaest, Vermeir, and
Omey (2015), Baert et al. (2020), Moens, Baert, Verhofstadt, and Van Ootegem.
(2019) and Morgeson and Humphrey (2006).
25Table 2. Perceived Career-related Fears Induced by the COVID-19 Crisis: Regression Results
Fear % with Significantly more pronounced if … Significantly less pronounced if …
fear
Losing job in the 21.1% Female; older age; migration background; province of Flemish Brabant; Better current health; more secure contract (public sector or permanent contract in
short or long term sector is catering and tourism; more dependent on others in job; private sector); longer tenure with current employer; more satisfied with job; more
temporarily unemployed. feedback from others in job; sector is provision of services, financial, health, ICT,
agriculture and horticulture or government.
Losing job in the 13.7% Female; older age; province of Flemish Brabant; sector is catering and Better current health; more secure contract (public sector or permanent contract in
short term tourism or sales; temporarily unemployed; higher % of work potentially private sector); longer tenure with current employer; more satisfied with job; more
done via telework. feedback from others in job; sector is provision of services, financial, health, ICT,
agriculture and horticulture, maintenance, education or government.
Missing out on 26.2% Migration background; province of Flemish Brabant; more interaction Older age; tertiary education; better current health; more secure contract (public
promotion outside of the organisation in job; sector is catering and tourism, sector or permanent contract in private sector); part-time contract; more satisfied
human resources, ICT, legal, logistics and transport, production or with job; sector is health.
technology; temporarily unemployed.
Overall negative 33.6% Female; older age; province of West Flanders; province of Flemish Better current health; more secure contract (public sector or permanent contract in
impact on career Brabant; better health before the COVID-19 crisis; more dependent on private sector); longer tenure with current employer; more satisfied with job; more
others in job or more interaction outside of the organisation in job; feedback from others in job; sector is health or government.
sector is catering and tourism; temporarily unemployed.
Negative impact on 49.9% Higher number of resident children; province of West Flanders; COVID- In a relationship and cohabiting; better current health; more secure contract (public
wage 19 patient in the recent past (probably); more interaction outside of the sector or permanent contract in private sector); more satisfied with job; more
organisation in job; sector is catering and tourism; temporarily feedback from others in job; sector is health or government.
unemployed.
Negative impact on 27.5% Living in the suburbs of a city; better health before the COVID-19 crisis; Older age; better current health; more satisfied with job.
personal motivation more dependent on others in job.
Negative impact on 51.9% Tertiary education; province of West Flanders; province of East Female; older age; better current health; more secure contract (public sector or
the number of Flanders; better health before the COVID-19 crisis; more dependent on permanent contract in private sector); more satisfied with job; more feedback from
attractive vacancies others in job; sector is creative or marketing; temporarily unemployed. others in job; sector is health, ICT, agriculture and horticulture or maintenance.
Notes. The proportion ‘with fear’ corresponds to the sum of those who indicated ‘completely agree’ and ‘somewhat agree’ to the related survey item (see Appendix A). The relationship to the
personal and job characteristics was analysed by means of a linear regression analysis with heteroscedasticity-robust standard errors (in which all characteristics mentioned in Table 1 were included).
The significance level was set as p < 0.05. N = 3,821.
26Table 3. Perceived Evolution in Attaching Importance to Particular Job Aspects Induced by the COVID-19 Crisis: Regression Results
Aspect % attaching more Significantly more pronounced if … Significantly less pronounced if …
importance to
aspect
Wage 20.6% More interaction outside of the organisation in job. Older age; tertiary education; in a relationship and
cohabiting; temporarily extended telework; sector is
research and development.
Employment 41.7% More secure contract (public sector or permanent contract in private sector); more Older age; province of East Flanders; living in the centre of a
relationship interaction outside of the organisation in job; higher % of work potentially done via village; better current health; more satisfied with job; more
telework. feedback from others in job.
Job content 36.8% More interaction outside of the organisation in job; sector is education. In a relationship and cohabiting; more satisfied with job;
more feedback from others in job.
Working 51.8% Sector is health; higher % of work potentially done via telework. Tertiary education; living in the centre of a city; better
conditions current health; more satisfied with job; more feedback from
others in job.
Work-life 51.1% Higher number of resident children; COVID-19 patient at the moment (probably); more Tertiary education; living in the centre of a village; living in
balance dependent on others in job; sector is creative, health or education; higher % of work the centre of a city; better current health; more satisfied
potentially done via telework. with job; more autonomous in job; more feedback from
others in job.
Distance to the 41.2% Older age; temporarily unemployed. Tertiary education; resident others (not family); living in the
workplace centre of a village; more satisfied with job; sector is catering
and tourism.
Possibility of 48.1% Female; better health before the COVID-19 crisis; more secure contract (public sector or Older age; living in the centre of a city; better current health;
teleworking permanent contract in private sector); sector is administration, financial or management; more satisfied with job; more feedback from others in job.
temporarily unemployed; higher % of work potentially done via telework; temporarily
extended telework.
Notes. The proportion ‘attaching more importance’ corresponds to the sum of those who indicated ‘certainly more important’ and ‘somewhat more important’ to the related survey item (see
Appendix A). The relationship to the personal and job characteristics was analysed by means of a linear regression analysis with heteroscedasticity-robust standard errors (in which all characteristics
mentioned in Table 1 were included). The significance level was set as p < 0.05. N = 3,821.
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